JAVA识别图形验证码

最近一直在开发一个用于自动发帖的工具，用HttpClient模拟客户端浏览器注册发帖。但是碰到了图形验证码的问题了，对单数字的验证码，通过一些OCR引擎，如：tesseract，AspriseOCR很容易解决问题。但碰到如CSDN论坛这中图形验证码就比较麻烦，必须先通过预处理。使图象二值化，黑白灰度，增加亮度。我的代码如下：

package myfilter;

import java.io.*;

import java.awt.image.*;

import java.awt.geom.AffineTransform;

import java.awt.color.ColorSpace;

import java.awt.image.ConvolveOp;

import java.awt.image.Kernel;

import java.awt.image.BufferedImage;

import javax.imageio.ImageIO;

import java.awt.Toolkit;

import java.awt.Image;

public class MyImgFilter {

BufferedImage image;

private int iw, ih;

private int[] pixels;

public MyImgFilter(BufferedImage image) {

this.image = image;

iw = image.getWidth();

ih = image.getHeight();

pixels = new int[iw * ih];

}

public BufferedImage changeGrey() {

PixelGrabber pg = new PixelGrabber(image.getSource(), 0, 0, iw, ih, pixels,0, iw);

try {

pg.grabPixels();

} catch (InterruptedException e) {

e.printStackTrace();

}

// 设定二值化的域值，默认值为100

int grey = 100;

// 对图像进行二值化处理，Alpha值保持不变

ColorModel cm = ColorModel.getRGBdefault();

for (int i = 0; i < iw * ih; i++) {

int red, green, blue;

int alpha = cm.getAlpha(pixels[i]);

if (cm.getRed(pixels[i]) > grey) {

red = 255;

} else {

red = 0;

}

if (cm.getGreen(pixels[i]) > grey) {

green = 255;

} else {

green = 0;

}

if (cm.getBlue(pixels[i]) > grey) {

blue = 255;

} else {

blue = 0;

}

pixels[i] = alpha << 24 | red << 16 | green << 8 | blue; //通过移位重新构成某一点像素的RGB值

}

// 将数组中的象素产生一个图像

Image tempImg=Toolkit.getDefaultToolkit().createImage(new MemoryImageSource(iw,ih, pixels, 0, iw));

image = new BufferedImage(tempImg.getWidth(null),tempImg.getHeight(null), BufferedImage.TYPE_INT_BGR );

image.createGraphics().drawImage(tempImg, 0, 0, null);

return image;

}

public BufferedImage getMedian() {

PixelGrabber pg = new PixelGrabber(image.getSource(), 0, 0, iw, ih,

pixels,

0, iw);

try {

pg.grabPixels();

} catch (InterruptedException e) {

e.printStackTrace();

}

// 对图像进行中值滤波，Alpha值保持不变

ColorModel cm = ColorModel.getRGBdefault();

for (int i = 1; i < ih - 1; i++) {

for (int j = 1; j < iw - 1; j++) {

int red, green, blue;

int alpha = cm.getAlpha(pixels[i * iw + j]);

// int red2 = cm.getRed(pixels[(i - 1) * iw + j]);

int red4 = cm.getRed(pixels[i * iw + j - 1]);

int red5 = cm.getRed(pixels[i * iw + j]);

int red6 = cm.getRed(pixels[i * iw + j + 1]);

// int red8 = cm.getRed(pixels[(i + 1) * iw + j]);

// 水平方向进行中值滤波

if (red4 >= red5) {

if (red5 >= red6) {

red = red5;

} else {

if (red4 >= red6) {

red = red6;

} else {

red = red4;

}

}

} else {

if (red4 > red6) {

red = red4;

} else {

if (red5 > red6) {

red = red6;

} else {

red = red5;

}

}

}

int green4 = cm.getGreen(pixels[i * iw + j - 1]);

int green5 = cm.getGreen(pixels[i * iw + j]);

int green6 = cm.getGreen(pixels[i * iw + j + 1]);

// 水平方向进行中值滤波

if (green4 >= green5) {

if (green5 >= green6) {

green = green5;

} else {

if (green4 >= green6) {

green = green6;

} else {

green = green4;

}

}

} else {

if (green4 > green6) {

green = green4;

} else {

if (green5 > green6) {

green = green6;

} else {

green = green5;

}

}

}

// int blue2 = cm.getBlue(pixels[(i - 1) * iw + j]);

int blue4 = cm.getBlue(pixels[i * iw + j - 1]);

int blue5 = cm.getBlue(pixels[i * iw + j]);

int blue6 = cm.getBlue(pixels[i * iw + j + 1]);

// int blue8 = cm.getBlue(pixels[(i + 1) * iw + j]);

// 水平方向进行中值滤波

if (blue4 >= blue5) {

if (blue5 >= blue6) {

blue = blue5;

} else {

if (blue4 >= blue6) {

blue = blue6;

} else {

blue = blue4;

}

}

} else {

if (blue4 > blue6) {

blue = blue4;

} else {

if (blue5 > blue6) {

blue = blue6;

} else {

blue = blue5;

}

}

}

pixels[i * iw +

j] = alpha << 24 | red << 16 | green << 8 | blue;

}

}

// 将数组中的象素产生一个图像

Image tempImg=Toolkit.getDefaultToolkit().createImage(new MemoryImageSource(iw,ih, pixels, 0, iw));

image = new BufferedImage(tempImg.getWidth(null),tempImg.getHeight(null), BufferedImage.TYPE_INT_BGR );

image.createGraphics().drawImage(tempImg, 0, 0, null);

return image;

}

public BufferedImage getGrey() {

ColorConvertOp ccp=new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_GRAY), null);

return image=ccp.filter(image,null);

}

//Brighten using a linear formula that increases all color values

public BufferedImage getBrighten() {

RescaleOp rop=new RescaleOp(1.25f, 0, null);

return image=rop.filter(image,null);

}

//Blur by "convolving" the image with a matrix

public BufferedImage getBlur() {

float[] data = {

.1111f, .1111f, .1111f,

.1111f, .1111f, .1111f,

.1111f, .1111f, .1111f, };

ConvolveOp cop = new ConvolveOp(new Kernel(3, 3, data));

return image=cop.filter(image,null);

}

// Sharpen by using a different matrix

public BufferedImage getSharpen() {

float[] data = {

0.0f, -0.75f, 0.0f,

-0.75f, 4.0f, -0.75f,

0.0f, -0.75f, 0.0f};

ConvolveOp cop = new ConvolveOp(new Kernel(3, 3, data));

return image=cop.filter(image,null);

}

// 11) Rotate the image 180 degrees about its center point

public BufferedImage getRotate() {

AffineTransformOp atop=new AffineTransformOp(AffineTransform.getRotateInstance(Math.PI,image.getWidth()/2,image.getHeight()/2),

AffineTransformOp.TYPE_NEAREST_NEIGHBOR);

return image=atop.filter(image,null);

}

public BufferedImage getProcessedImg()

{

return image;

}

public static void main(String[] args) throws IOException {

FileInputStream fin=new FileInputStream(args[0]);

BufferedImage bi=ImageIO.read(fin);

MyImgFilter flt=new MyImgFilter(bi);

flt.changeGrey();

flt.getGrey();

flt.getBrighten();

bi=flt.getProcessedImg();

String pname=args[0].substring(0,args[0].lastIndexOf("."));

File file = new File(pname+".jpg");

ImageIO.write(bi, "jpg", file);

}

}

运行java myfilter.MyImgFilter t6.bmp，请确认图片t6.bmp与myfilter目录在同一目录下。

顺便说一下，在JDK1.5下，ImageIO可以输出JPG，BMP，PNG三种格式图片，但不支持GIF图片输出。